Progressively Censored Rayleigh Data under Bayesian Estimation

Abstract

Present study is proposed some Bayes estimators for unknown scale parameter of Rayleigh distribution based on two different loss functions. Both the Progressively Type-II and conventional Type-II censored data has been used for estimation under the Jeffrey's extension prior. The One-Sided Bayes prediction bound lengths are also determine. A numerical study carried out for the analysis of proposed Bayes estimators in terms of their risk ratios under a real data set and under a simulation study.